new tensor connections

source/XLink.cpp

@@ -21,6 +21,7 @@
 
 #include <stdio.h>
 #include "XLink.h"
+#include "XName.h"
 
 namespace nts{ // namespace nts(NiuTrans.Tensor)
 
@@ -35,6 +36,7 @@ XLink::XLink()
     tailNum  = 0;
     paramNum = 0;
     type[0] = 0;
+    typeID = 0;
 }
     
 /* deconstructor */
@@ -59,14 +61,14 @@ void XLink::Reset()
 
 /* 
 set edge type name 
->> typeName - type name in string
+>> id - id of the type
 */
-void XLink::SetType(const char * typeName)
+void XLink::SetType(int id)
 {
     type[0] = 0;
-    if(typeName == NULL)
-        return;
-    strcpy(type, typeName);
+    strcpy(type, GetOPName(id));
+    typeID = id;
+    CheckNTErrors(!strcmp(type, "NULL"), "illegal edge type name!");
 }
 
 /* 
@@ -141,9 +143,9 @@ create a hyperedge with two input tensors and a output tensor
 >> t1 - a tail tensor
 >> t2 - another tail tensor
 >> h - head tensor
->> typeName - name of edge type
+>> id - id of the edge type
 */
-void XLink::MakeLink(XTensor * t1, XTensor * t2, XTensor * h, const char * typeName)
+void XLink::MakeLink(XTensor * t1, XTensor * t2, XTensor * h, int id)
 {
     if(h != NULL)
         return;
@@ -159,7 +161,7 @@ void XLink::MakeLink(XTensor * t1, XTensor * t2, XTensor * h, const char * typeN
     else{
         ShowNTErrors("TODO!");
     }
-    income.SetType(typeName);
+    income.SetType(id);
 
     /* backward for t1 */
     if(t1 != NULL){
@@ -180,15 +182,15 @@ void XLink::MakeLink(XTensor * t1, XTensor * t2, XTensor * h, const char * typeN
 create a hyper edge with a list of tensors and a output tensor 
 >> list - a list of input tensors
 >> h - head tensor
->> typeName - name of edge type
+>> id - id of the edge type
 */
-void XLink::MakeLink(XList * list, XTensor * h, const char * typeName)
+void XLink::MakeLink(XList * list, XTensor * h, int id)
 {
     /* forward */
     XLink &income = h->income;
     income.Reset();
     income.SetHead(h);
-    income.SetType(typeName);
+    income.SetType(id);
 
     for(int i = 0; i < list->count; i++){
         XTensor * t = (XTensor*)list->GetItem(i);

source/XLink.h

@@ -74,6 +74,9 @@ struct XLink
     /* name of the hyperedge type. e.g., sum, mul ... */
     char type[MAX_OP_NAME_LENGTH];
     
+    /* type id */
+    int typeID;
+    
     /* constuctor */
     XLink();
     
@@ -83,8 +86,8 @@ struct XLink
     /* reset it */
     void Reset();
 
-    /* set edge type name */
-    void SetType(const char * typeName);
+    /* set edge type id and name */
+    void SetType(int id);
 
     /* set head */
     void SetHead(XTensor * h);
@@ -103,11 +106,11 @@ struct XLink
 
     /* create a hyper edge with two input tensors and a output tensor */
     static
-    void MakeLink(XTensor * t1, XTensor * t2, XTensor * h, const char * typeName);
+    void MakeLink(XTensor * t1, XTensor * t2, XTensor * h, int id);
 
-    /* create a hyper edge with a list of tensors and a output tensor */
+    /* create a hyper edge with a list of input tensors and a output tensor */
     static
-    void MakeLink(XList * list, XTensor * h, const char * typeName);
+    void MakeLink(XList * list, XTensor * h, int id);
 
     /* add a parameter */
     static
@@ -120,4 +123,4 @@ struct XLink
     
 } // namespace nts(NiuTrans.Tensor)
 
-#endif // __XLINK_H__
\ No newline at end of file
+#endif // __XLINK_H__

source/XName.cpp

+/* NiuTrans.Tensor - an open-source tensor library
+ * Copyright (C) 2018, Natural Language Processing Lab, Northestern University.
+ * All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/*
+ * $Created by: XIAO Tong (xiaotong@mail.neu.edu.cn) 2018-07-05
+ */
+
+#ifndef __XNAME_H__
+#define __XNAME_H__
+
+namespace nts { // namespace nts(NiuTrans.Tensor)
+    
+#define MATH_ARITHMETIC     0x00001000
+#define MATH_SUM            MATH_ARITHMETIC + 1
+#define MATH_MULTIPLY       MATH_SUM + 1
+    
+/* get operator name */
+const char * GetOPName(int type)
+{
+    if((type & MATH_ARITHMETIC) != 0){
+        if(type == MATH_SUM)
+            return "M_SUM";
+        else if(type == MATH_MULTIPLY)
+            return "M_MULTIPLY";
+    }
+    
+    return "NULL";
+}
+    
+} // namespace nts(NiuTrans.Tensor)
+
+#endif // __XNAME_H__

source/XName.h

@@ -20,7 +20,7 @@
  * We define various names here
  *
  * $Created by: XIAO Tong (xiaotong@mail.neu.edu.cn) 2018-07-05
- * It was really HOT these days. I can't imagine what a hot day here in Shenyang!
+ * It was really HOT these days. I can't imagine it is SO hot here in Shenyang!
 */
 
 #ifndef __XNAME_H__
@@ -28,22 +28,13 @@
 
 namespace nts { // namespace nts(NiuTrans.Tensor)
 
-#define MATH_MATMUL "M_MATMUL"
-#define MATH_CONCATENATESOLY "M_CONCATENATESOLY"
-#define MATH_COPYVALUES "M_COPYVALUES"
-#define MATH_MATRIXMUL "M_MATRIXMUL"
-#define MATH_MATRIXMUL2D "M_MATRIXMUL2D"
-#define MATH_MATRIXMULBATCHED "M_MATRIXMULBATCHED"
-#define MATH_MERGE "M_MERGE"
-#define MATH_MULTIPLY "M_MULTIPLY"
-#define MATH_REDUCEMAX "M_REDUCEMAX"
-#define MATH_REDUCESUM "M_REDUCESUM"
-#define MATH_SELECTRANGE "M_SELECTRANGE"
-#define MATH_SORT "M_SORT"
-#define MATH_SUM "M_SUM"
-#define MATH_TOPK "M_TOPK"
-#define MATH_UNSQUEEZE "M_UNSQUEEZE"
+#define MATH_ARITHMETIC     10000
+#define MATH_SUM            MATH_ARITHMETIC + 1
+#define MATH_MULTIPLY       MATH_SUM + 1
+
+/* get operator name */
+const char * GetOPName(int type);
 
 } // namespace nts(NiuTrans.Tensor)
 
-#endif // __XNAME_H__
\ No newline at end of file
+#endif // __XNAME_H__

source/core/arithmetic/MatrixMul2DParallel.cpp

@@ -40,9 +40,9 @@ where trans() return the transposed matrix if the flag is fired
 >> parallelRunner - parallel processing module
 */
 void MatrixMul2DParallel(XTensor * a, MATRIX_TRANS_TYPE transposedA,
-    XTensor * b, MATRIX_TRANS_TYPE transposedB,
-    XTensor * c, DTYPE alpha, DTYPE beta,
-    XPRunner * parallelRunner)
+                         XTensor * b, MATRIX_TRANS_TYPE transposedB,
+                         XTensor * c, DTYPE alpha, DTYPE beta,
+                         XPRunner * parallelRunner)
 {
     CheckNTErrors((a && b && c), "Empty input tensors!");
     CheckNTErrors((a->order == 2 && b->order == 2 && c->order == 2),

source/core/arithmetic/Sum.cpp

@@ -21,6 +21,7 @@
 
 #include "../../XTensor.h"
 #include "../../XName.h"
+#include "../../XUtility.h"
 #include "Sum.h"
 #include "Sum.cuh"
 
@@ -28,12 +29,13 @@ namespace nts { // namespace nts(NiuTrans.Tensor)
 
 /*
 tensor summation c = a + b * \beta
+return a pointer
 >> a - a tensor
 >> b - another tensor
 >> c - where we put a+b*\beta. we save it in a if c is NULL
 >> beta - the scaling factor
 */
-void Sum(XTensor * a, XTensor * b, XTensor * c, DTYPE beta)
+void _Sum(XTensor * a, XTensor * b, XTensor * c, DTYPE beta)
 {
     if (c == NULL)
         c = a;
@@ -59,17 +61,16 @@ void Sum(XTensor * a, XTensor * b, XTensor * c, DTYPE beta)
                 ShowNTErrors("Cannot run this method on multiple devices simultaneously!");
             }
             else
-                CudaSum(a, b, c, beta);
+                _CudaSum(a, b, c, beta);
         }
         else
-            CudaSum(a, b, c, beta);
+            _CudaSum(a, b, c, beta);
 
 #endif
     }
     else {
         if (!a->isSparse && !b->isSparse) {
-            CheckNTErrors(!c->isSparse,
-                "Illegal use of sparse matrix in addition!");
+            CheckNTErrors(!c->isSparse, "Illegal use of sparse matrix in addition!");
     
             if (a->dataType == DEFAULT_DTYPE &&
                 b->dataType == DEFAULT_DTYPE &&
@@ -112,5 +113,38 @@ void Sum(XTensor * a, XTensor * b, XTensor * c, DTYPE beta)
         }
     }
 }
+    
+/*
+tensor summation a = a + b * \beta
+do it on site
+>> a - a tensor
+>> b - another tensor
+>> beta - the scaling factor
+*/
+void _SumMe(XTensor * a, XTensor * b, DTYPE beta)
+{
+    _Sum(a, b, a, beta);
+}
+    
+/*
+tensor summation a = a + b * \beta
+return a XTensor structure
+>> a - a tensor
+>> b - another tensor
+>> beta - the scaling factor
+*/
+XTensor Sum(XTensor &a, XTensor &b, DTYPE beta)
+{
+    XTensor c(&a);
+    
+    /* computation */
+    _Sum(&a, &b, &c, beta);
+    
+    /* tensor connections */
+    //XLink::MakeLink(&a, &b, &c, MATH_SUM);
+    //XLink::AddParamToHead(&c, beta);
+    
+    return c;
+}
 
 } // namespace nts(NiuTrans.Tensor)

source/core/arithmetic/Sum.cu

@@ -51,7 +51,7 @@ tensor summation c = a + b * \beta (cuda version)
 >> c - where we put a+b*\beta. we save it in a if c is NULL
 >> beta - the scaling factor
 */
-void CudaSum(XTensor * a, XTensor * b, XTensor * c, DTYPE beta)
+void _CudaSum(XTensor * a, XTensor * b, XTensor * c, DTYPE beta)
 {
     if (c == NULL)
         c = a;
@@ -124,7 +124,7 @@ tensor summation c = a + b * \beta (cuda version) with an input handle
 >> size - size of the array
 >> beta - the coefficient
 */
-void CudaSumWithHandle(int devID, cublasHandle_t * handle, DTYPE * a, DTYPE * b, DTYPE * c, int size, DTYPE beta)
+void _CudaSumWithHandle(int devID, cublasHandle_t * handle, DTYPE * a, DTYPE * b, DTYPE * c, int size, DTYPE beta)
 {
     if (size == 0)
         return;
@@ -160,4 +160,4 @@ void CudaSumWithHandle(int devID, cublasHandle_t * handle, DTYPE * a, DTYPE * b,
 
 #endif // USE_CUDA
 
-} // namespace nts(NiuTrans.Tensor)
\ No newline at end of file
+} // namespace nts(NiuTrans.Tensor)

source/core/arithmetic/Sum.cuh

@@ -34,14 +34,14 @@ void KernelADD(DTYPE * a, DTYPE * b, DTYPE * c, int size, DTYPE beta = (DTYPE)1.
 
 /* tensor summation c = a + b * \beta (cuda version) */
 extern "C"
-void CudaSum(XTensor * a, XTensor * b, XTensor * c = NULL, DTYPE beta = (DTYPE)1.0);
+void _CudaSum(XTensor * a, XTensor * b, XTensor * c = NULL, DTYPE beta = (DTYPE)1.0);
 
 /*  tensor summation c = a + b * \beta (cuda version) with an input handle */
 extern "C"
-void CudaSumWithHandle(int devID, cublasHandle_t * handle, DTYPE * a, DTYPE * b, DTYPE * c, int size, DTYPE beta = (DTYPE)1.0);
+void _CudaSumWithHandle(int devID, cublasHandle_t * handle, DTYPE * a, DTYPE * b, DTYPE * c, int size, DTYPE beta = (DTYPE)1.0);
 
 #endif // USE_CUDA
 
 } // namespace nts(NiuTrans.Tensor)
 
-#endif // __SUM_CUH__
\ No newline at end of file
+#endif // __SUM_CUH__

source/core/arithmetic/Sum.h

 /* NiuTrans.Tensor - an open-source tensor library
-* Copyright (C) 2017, Natural Language Processing Lab, Northestern University.
-* All rights reserved.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*   http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
+ * Copyright (C) 2018, Natural Language Processing Lab, Northestern University.
+ * All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
 
 /*
-* $Created by: XIAO Tong (email: xiaotong@mail.neu.edu.cn) 2018-04-24
-*/
+ * $Created by: XIAO Tong (email: xiaotong@mail.neu.edu.cn) 2018-04-24
+ */
 
 #ifndef __SUM_H__
 #define __SUM_H__
@@ -27,9 +27,14 @@
 namespace nts { // namespace nts(NiuTrans.Tensor)
 
 /* tensor summation c = a + b * \beta */
-extern "C"
-void Sum(XTensor * a, XTensor * b, XTensor * c = NULL, DTYPE beta = (DTYPE)1.0);
+void _Sum(XTensor * a, XTensor * b, XTensor * c = NULL, DTYPE beta = (DTYPE)1.0);
+
+/* tensor summation a = a + b * \beta (return a pointer) */
+void _SumMe(XTensor * a, XTensor * b, DTYPE beta = (DTYPE)1.0);
+    
+/* tensor summation c = a + b * \beta (return a structure) */
+XTensor Sum(XTensor &a, XTensor &b, DTYPE beta = (DTYPE)1.0);
 
 } // namespace nts(NiuTrans.Tensor)
 
-#endif // __SUM_H__
\ No newline at end of file
+#endif // __SUM_H__

source/core/movement/CopyValues.cpp

@@ -42,9 +42,6 @@ bool CopyValues(XTensor * s, XTensor * t, XStream * stream)
     CheckNTErrors((t->data != NULL), "Cannot copy to an empty data array!");
     CheckNTErrors((s->unitNum == t->unitNum), "Unmatched data item number!");
 
-    /* make tensor connections */
-    XLink::MakeLink(s, NULL, t, MATH_COPYVALUES);
-
     if ((s->dataType == X_FLOAT16 && t->dataType == X_FLOAT) ||
         (s->dataType == X_FLOAT && t->dataType == X_FLOAT16)) {
         CheckNTErrors(((s->devID < 0 && t->devID < 0) || s->devID == t->devID),

source/core/shape/ConcatenateSolely.cpp

@@ -37,10 +37,6 @@ void ConcatenateSolely(XList * smalls, XTensor * big, int dim)
 {
     CheckNTErrors((big->order > dim && dim >= 0), "Illegal dimension to concatenate!");
 
-    /* make tensor connections */
-    XLink::MakeLink(smalls, big, MATH_CONCATENATESOLY);
-    XLink::AddParamToHeadInt(big, dim);
-
     int catDimSize = 0;
     int dimRDI = big->order - dim - 1;
 
@@ -102,4 +98,4 @@ void ConcatenateSolely(XList * smalls, XTensor * big, int dim)
         delete sourceArrays;
     }
 }
-} // namespace nts(NiuTrans.Tensor)
\ No newline at end of file
+} // namespace nts(NiuTrans.Tensor)

source/core/utilities/XMatrixSegment.cpp

@@ -36,7 +36,7 @@ segment a 2d tensor (i.e., matrix) into blocks and run jobs in parallel
 >> ... - arguments of the jobs
 */
 void RunParallel2D(XPRunner * parallelRunner, void * job,
-    int opNum, int rowNum, int colNum, int argNum, ...)
+                   int opNum, int rowNum, int colNum, int argNum, ...)
 {
     if (rowNum == 0 || colNum == 0)
         return;

source/test/TSum.cpp

@@ -55,7 +55,7 @@ bool TestSum1()
     b->SetData(bData, unitNum);
 
     /* call sum function */
-    Sum(a, b);
+    _Sum(a, b);
 
     /* check results */
     cpuTest = a->CheckData(answer, unitNum);
@@ -131,7 +131,7 @@ bool TestSum2()
     c->SetZeroAll();
 
     /* call Sum function */
-    Sum(a, b, c, beta);
+    _Sum(a, b, c, beta);
 
     /* check results */
     cpuTest = c->CheckData(answer, unitNum);